Blind Panoramic Image Quality Assessment via the Asymmetric Mechanism of Human Brain

Xia, Yumeng; Wang, Yongfang; Ye, Peng

doi:10.1109/vcip47243.2019.8965887

Cited by 10 publications

(1 citation statement)

References 17 publications

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“…For NR models, BRISQUE, NIQE, BMPRI, 34 DB-CNN, 17 and GM-LOG-BIQA 35 are noted as the NR-IQA methods. We also compare performance with NR-OIQA models, such as ASY-PIQA, 36 SSP-BOIQA, 12 MC360IQA, DDAMN, 37 and MP-BOIQA with PLCC, SRCC, and RMSE index. The performance contrast consequences between this work and other methods are shown in the CVIQD and OIQA databases in Tables 1 and 2.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

Multifaceted perception-based blind omnidirectional image quality assessment

Liu,

Wang,

Jiang

et al. 2023

J. Electron. Imag.

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With the rapid development of computer vision, the omnidirectional image (OI) with a broader view and a higher resolution provides humans with an immersive visual experience and has attracted more researchers' attention. But current image quality assessment models cannot perform well due to neglecting the difference between panoramic images and traditional images, limiting OIs' further development. Inspired by the above problem, we propose a blind OI quality assessment model based on multi-frequency features, color features, and human visual system-based saliency features. Specifically, we utilize the high-and low-frequency information mapped to the frequency domain to measure the frequency domain loss. The local binary pattern operator is applied to encode the different color channel information. Then the local natural scene statistics and entropy features are extracted using the input image to weight the obtained saliency image by our model to reduce the model's computational complexity. Finally, support vector regression is employed to predict the OIs' quality scores. Experimental results on CVIQD and OIQA databases prove that our work performs better than state-of-the-art OIQA models.

show abstract

Section: Experimental Results and Analysismentioning

confidence: 99%

Multifaceted perception-based blind omnidirectional image quality assessment

Liu,

Wang,

Jiang

et al. 2023

J. Electron. Imag.

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show abstract

Perceptual quality assessment of panoramic stitched contents for immersive applications: a prospective survey

Ullah

Afzal

Khan

2022

Virtual Reality & Intelligent Hardware

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No‐Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics

Yu,

Yang,

Liu

et al. 2024

IET Signal Processing

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High dynamic range omnidirectional image (HOI) can provide more real and immersive watching experience for viewers, thus has become an important presentation of virtual reality technology. However, both the system processing and the characteristics of HOI make the design of HOI quality metric (HOIQM) a challenging issue. In this work, considering the difference between whole field of view (FoV) and viewer‐selected viewport, distortion features from both global and local perspectives are extracted, and a blind HOIQM is proposed. Specifically, because different regions have different projections in SSP projection, we have constructed the optimal bivariate response pair in the equatorial region and bipolar region according to their projection direction, and parameters in the BGGD based‐spatial oriented correlation model are extracted as global statistical features. Meanwhile, combined with the visual perception for HOI, the key blocks are determined in equatorial region, and the local statistical characteristics of the key blocks are extracted by analyzing the distribution of multiscale structure information. Finally, the global and local features are regressed by SVR to obtain the final HOI quality. Experimental results on NBU‐HOID database demonstrate that the proposed quality metric is outperformed the existing representative quality metrics and is more consistent with human visual perception for HOI.

show abstract

Blind Panoramic Image Quality Assessment via the Asymmetric Mechanism of Human Brain

Cited by 10 publications

References 17 publications

Multifaceted perception-based blind omnidirectional image quality assessment

Multifaceted perception-based blind omnidirectional image quality assessment

Perceptual quality assessment of panoramic stitched contents for immersive applications: a prospective survey

No‐Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics

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